Dedicated to the Cargo Cults of Biology Science, Biotechnology and the Pharmaceutical Industry.
"So we really ought to look into theories that don't work, and science that isn't science"
Richard Feynman,
Cargo Cult Science,
From a Caltech commencement address given in 1974

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Monday, August 29, 2011

Next came the patents. The news that came out today is that the U.S. Patent and Trademark Office (USPTO) has issued a Notice of Allowance for our patent application.

A primary advantage of this patented peptide library is the ability to rapidly screen and identify novel peptides that exhibit cell specific targeting characteristics for directed delivery of nucleic acid therapeutics," said the Chief Scientific Officer. "Delivery remains a significant challenge in the nucleic acid therapeutic space, and peptides with high affinity and specificity are expected to be a fundamental component to developing delivery approaches to a wide spectrum of tissues and cell types. In addition, the library may also be exploited to screen for peptides that function as specific antagonists, agonists or generally exhibit drug like properties.

The only problem is that the library has no ability to do the things described above. It was a dud. The obedient workers did everything they could but they couldn't get the results that validate the statements of the Chief Scientific Officer quoted here.

The CSO didn't mention that the team who developed and tested the library were sacked. They needed to go out and find someone who could figure out what to do with that library.

There are very few people with the expertise and resources to perform this kind of science.

"What to do with it?" was always the question. There was no conversation about "what to do with it" other than use it to target this cell or that cell. But how? That was the scientific "wealth into the system" that Feynman speaks of. Everything else was what Kurt Vonnegut referred to as "Kit Science" in Cat's Cradle. We had molecular biology kits, phage display kits, and we did some cell culture work. We got our patents and paper. But what should we have done with the library?

A lot of scientists I've worked with believe that there is some clever thing we didn't think of. When we got the orders to test the library against specific cells there was no discussion about the possibility that it wouldn't work. We tested the random thoughts of the leaders, various methods of treating the cells, different buffers and so on. When about 100 random thoughts had been tested they told us to go home. It was a relief.

But it doesn't work. No airplanes land. So
I call these things cargo cult science, because they follow all the
apparent precepts and forms of scientific investigation, but
they're missing something essential, because the planes don't land.

Now it behooves me, of course, to tell you what they're missing.
But it would be just about as difficult to explain to the South Sea
Islanders how they have to arrange things so that they get some
wealth in their system. It is not something simple like telling
them how to improve the shapes of the earphones. But there is one
feature I notice that is generally missing in cargo cult science.
That is the idea that we all hope you have learned in studying
science in school--we never explicitly say what this is, but just
hope that you catch on by all the examples of scientific
investigation.

The CSO makes the claim that "peptides with high affinity and specificity are expected to be a fundamental component to developing delivery approaches to a wide spectrum of tissues and cell types". Why are they expected to contribute to this Holy Grail of RNAi technology? How will it work? Feynman also said:

You can know the name of a bird in all the languages of the world, but when you're finished, you'll know absolutely nothing whatever about the bird... So let's look at the bird and see what it's doing -- that's what counts.

I think of the peptide in this library as the name of a bird. They are looking for that name spelled out in amino acid letters. But even if they find it they will still know nothing about the peptide. They have to see what it's doing. How will they do that? Once again, "what to do with it?". Who will ask the question?

There is nothing wrong with not knowing something. That is why we do research. The problem comes when we want to believe something so much that we accept false answers. This library is just a library. It was not conceived of by someone who had any idea what to do with it. That person, and all of the others are gone now. The CSO quoted above inherited the library and he doesn't know what to do with it. Somehow he's figured out that it will be fundamental to solving the RNAi delivery problem. How will he know when they've found the magic RNAi delivery peptide? I guess they'll know it when they see it.

Friday, August 26, 2011

Monday, August 22, 2011

Magic is the only honest profession. The pricing of Seattle Genetics new drug is an example of dishonesty in the biotechnology industry. Clay Siegall, their CEO, is good at the art of deception. He holds a PhD and a large number of patents and publications. You might be lead to believe that he is a scientist. He is actually a businessman. He tells you his company is dedicated to unmet medical needs. That is the diversion. While we are patting them on the back for doing something to help mankind, they are plotting to charge us over 100K to have access to their drug.

The trick is not hard to do. The Invisible Gorilla is an example. In the invisible gorilla experiment there are people in white t-shirts and black t-shirts passing a basketball around. You are told to count the number of times the people in white t-shirts pass the ball to each other. While you are counting passes, someone in a gorilla suit walks through the scene. Most people seem to not see the gorilla because their attention has been diverted by the direction to count passes. You are tricked into not seeing something that is quite obvious once you know it is there.

This is how biotechnology operates, and much of the scientific community as well. Biotech CEOs and principal investigators do not wear white lab coats. They do not work in laboratories. They get noticed. They work very hard to gain a reputation that can be cashed in for money. Once the research grant or investment is in the bank, they go out and hire low paid obedient bachelor degreed servants to do the work. The only requirement is that the results must further the career of the leader.

We at the CCS are always looking for that gorilla walking past the screen. Go to the Seattle Genetics website and count white lab coats.

Did you see the businessmen deciding on the price of the drugs and the size of their bonuses?

Monday, August 15, 2011

The discussion of ideas is necessary for them to catch on. Watching TV or reading a book can be enjoyable but the best shows and books lead to further discussions. You get to participate in the seed that was planted. Watching NOVA or reading a Malcolm Gladwell book may enhance your ability to hold an intelligent conversation. It's up to you to surround yourself with people who also enjoy discussing new ideas. If you enjoy science, you should have friends who have something to share about the latest findings in Science or Nature or any of the other journals. Beyond the mandatory presentations and seminars, you should discuss the latest ideas.

I've had an epiphany on this very subject. I have no friends who enjoy exploring the absurdity of science as it is currently practiced. No one I know has anything negative to say about the profession of science. It seems impolite to be so negative about something that has a positive effect on our society such as science. I believe that only a small percentage of the ideas put forth by scientists ever amount to any greater understanding of our world. And that small percentage is very powerful. The other 95% of our ideas are not going to be useful. They may even be harmful. That 95% of BS deserves greater discussion.

For example, there is a paper out in Nature this week entitled "Broad neutralization coverage of HIV by multiple highly potent antibodies". The title itself seems unscientific. Using words like "highly potent" should be qualified in the conclusions of your paper. But that is the conversation I can't have.

Upon hearing about the HIV paper in Nature, I asked a friend if it would be a good idea to test the authors ability to identify their antibodies by coding each one (A, B, C... Q). Using the techniques reported in Nature, could they retake those measurements to identify each antibody. My friend was shocked that I was nothing but excited about how far science has advanced in HIV research. I said that I would be very excited if I could believe it were true. I was told I was just a skeptic. We did not discuss the paper, just the benefits of believing versus non-belief.

Every Sunday you will find churches full of people listening to a person discuss some aspect of the bible. That one book is discussed in a one way conversation by the preacher to the congregation. Later that conversation is carried on amongst the congregation. The better the sermon the more it will be discussed. Where do scientists gather on a weekly basis to discuss the latest findings? Usually, in the U.S., we gather in rooms where the lowest ranking "scientists" present their data to the highest ranking scientists. The direction of the conversation is taught in graduate school where the wannabe PhD "defends" his/her work to their committee. The preaching among scientists, in other words, is done from the pews, not the pulpit. Subsequent conversations are usually held by disgruntled grad students back at the laboratory, well out of the hearing range of a college professor. It is here where the real scientific conversations take place. Ideas are put forth to squash the dumb ideas. All of the proper controls are thought up. But rarely will those ideas be taken seriously unless they support the ideas of the preacher from the pew.

The mainstream idea to improve our world through science is to increase funding. The idea that I have today is to increase the discussion of scientific work. How to do it? If you read the Huffington Post, you will see that certain articles illicit more comments than others. What if there were a Huffington Post-like science blog where people could discuss work such as the latest HIV/AIDS paper in Nature? As we do with the work of social/economic engineers (our elected leaders) we can discuss the ideas and the merits of the scientific community leaders. Thought leaders such as Andrew Fire and Craig Mello can offer up their thoughts on why RNAi has been such a bust. Throw in a some comments from RNAi biotech CEOs and CSOs and see what the rest of us who are very interested in the subject have to say. We'll get into arguments and have an old fashioned debate, rather than the usual Lead Zepplins found in the journals. Break a paper down to pieces such as the IC50 measurements used in the HIV/AIDS Nature paper. Try and illicit a discussion on the measurements, the use of statistics, and the conclusions that can realistically be drawn. Highlight vested interests and how they effect certain outcomes. Talk about the "sexiness" of the research and how it enhances careers but increases the amount of BS being put forth. Highlight seemingly boring observations and how they can make a big difference.

The preachers from the pews do not seem to inspire. They conspire to keep bad information in the published journals so as to not hurt their careers. They have created a situation where laboratory work is looked down upon. Their greatest sin however, is that they are boring. They do not want the lower ranking members of science to discuss their work. They want us to read about how successful they were and thank them. If we don't believe them or we question them we are nattering nabobs. It flies in the face of what science is all about. If we want to know what really happened in the laboratory, we are going to have to let the people who actually do the work have a say. Let the people who read the papers and try to use them have a say. By increasing the level of talk surrounding science we'll increase the honesty.

Tuesday, August 09, 2011

An idealist is one who, on noticing that a rose smells better than a cabbage, concludes that it will also make better soup.

H. L. Mencken

Thought experiment: Executive Bill believes that siRNA can be used to knock out TNF alpha and reduce swelling in joints in rats and thus it will do the same in human beings.

Think of Executive Bill as a Martian who has come to the conclusion that humans will prefer rose soup over cabbage soup. He sends his little Martians out to prove him right.

By setting up such a complex hypothesis Bill has failed to acknowledge that the siRNA may not even be the proper molecule that mimics a naturally occurring small piece of RNA that will reduce gene expression. Smell alone may not predict food preference.We fool ourselves all through the hypothesis testing and reach the end point (where Executive Bill demands a full report in his office) with the false assumption that a human being should see a reduction in joint swelling. Executive Bill wants to know one thing, did the human see a reduction in joint swelling? Did the humans prefer rose soup?If the human sees an improvement, Executive Bill is vindicated. If there is no improvement, Executive Bill sends the scientists back into the lab to tweak the system.

In colloquial usage type I error might be called "failing to believe the truth". In biotechnology this is a common error when desired results do not match actual outcomes. Executive Bill will reject the truth (siRNA against TNA alpha has no effect on joint swelling) and send the scientists back to the lab to get the desired results. The Martian leader will send the little Martians back to earth to get them to prefer Rose Soup.

Type II error is "believing the falsehood". This would be the case if the data showed a reduction in joint swelling from the siRNA treatment when the siRNA had nothing to do with the reduction. Executive Bill would eagerly accept this type of error.

The Martian leader would eagerly accept any data that showed humans preferring Rose Soup. Let's say that the problem came from a mislabeling of the soups or fraud was committed by an ambitious little Martian. The desired results were obtained. They were false. They were accepted. Executive Bill and the Martian leader accept what they are being told.

In these two examples, siRNA and Rose Soup, we (the Cargo Cult Scientist) are saying that the non-erroneous outcome would be that siRNA has no effect on TNF alpha or anything in the human body, and that human beings will not eat Rose Soup. Our antagonists, Executive Bill and the Martian leaders' desired outcomes should be proven false. No matter what the outcome, they will only be accepting validation of their hypothesis. The easiest path to success, as defined by Bill and the Martian, is a type II error. Type I errors will be made until a type II can be arranged.

Now let's enter a superior being I will refer to as God. It is the Cargo Cult God and he needs to keep his subjects ignorant for amusement purposes. He delights in the folly of the minds who keep themselves fooled at all times. The Cargo Cult God wants to explain how Executive Bill and the Martian leader reach their status in their respective groups and how they maintain their positions. First, they are bullshitters and thus would use the truth if they could get to it. But getting to the truth would be a random act since they do not know how to conduct research. They begin from ignorance, either type I or type II errors or they are randomly yet unknowingly correct. They then select a desired outcome and draw a line from A) type I or II error or random correct assumption, to B) desired outcome. The desired outcome however cannot be attributed to the path of reasoning that is depicted by the line from A to B.

In 1974, Ian Mitroff and Tom Featheringham argued that "one of the most important determinants of a problem's solution is how that problem has been represented or formulated in the first place".

They defined type III errors as either the error of having solved the wrong problem when one should have solved the right problem or the error of choosing the wrong problem representation when one should have chosen the right problem representation.

In other words, Executive Bill set out to solve the problem of how to make siRNA into an anti-RA drug where he should have tried to solve the problem of determining the possibility of using siRNA as a drug in the first place. Maybe siRNA cannot survive in the human body.

Likewise, the Martian leader wanted to prove that Rose Soup would be preferable to Cabbage Soup. He should have conducted research on the relationship between the human senses of smell and taste.

In 2009, 'Dirty Rotten Strategies' by Ian I. Mitroff and Abraham Silvers was published regarding type III and type IV errors providing many examples of both developing good answers to the wrong questions (III) and deliberately selecting the wrong questions for intensive and skilled investigation (IV). Most of the examples have nothing to do with statistics, many being problems of public policy or business decisions.

The desired (i.e., non-erroneous) outcomes of a test are called true positive meaning "rejecting null hypothesis, when it is false" and true negative meaning "not rejecting null hypothesis, when it is true". What is the case when the desired outcome is not defined as non-erroneous?

Sunday, August 07, 2011

If you type 100 words a minute with ten years experience typing TPS forms on blue paper for ACME Products, what is your skill?

Typing

If you are the finance officer of a biotechnology company, what is your skill?

Finance

If you conduct research in a life science laboratory, what is your skill?

Research

The question however, is whether or not anyone conducts research in a biotechnology laboratory. Research is not about any particular piece of equipment or assay. An individual who can obtain a degree in science should have the ability to learn how to operate the various pieces of equipment. But biotechnology companies do not conduct research. The board will select the drug target and the antibody/siRNA or whatever is in fashion will be developed to address the target. Most often, they do not match target to technology and they one day will have to close up shop. What is missing is an understanding of research.

Research is an evolution. We begin with ignorance and evolve to understanding. Ignorance has an unpleasant connotation however, one that PhDs do not want associated with their work. Thus, they begin with an ignorance of their own ignorance. How many biotech PhDs have tried to make an antibody against amyloid beta? How many have used phage display to bind to amyloid beta? The concept is that they begin with the knowledge that something that binds to amyloid beta should prevent it from forming plaques in the brain and thus cure Alzheimer's patients. Research did not create that evolution of understanding. This stepwise cure for Alzheimer's has cost billions but has not panned out. There is something we don't know. We are still ignorant about the beginning of our research. Why are the plaques there?

As a result of the inability to admit our own ignorance, we have established a new paradigm for conducting research. We draw out mechanisms, such as we did with RNAi being used as a drug. The siRNA will enter the blood stream, go to its target and begin to reduce the translation of mRNA. Nothing else will happen and the target knock-out will cure or slow down the condition. Early on, it seemed that siRNA was knocking out targets. There was a leap of faith that this could be a drug. Since then we have a large body of evidence (both known and hidden from the light of day) that would lead us to think more about where this research emerged from. Did we begin from ignorance and evolve to understanding? It seems we began from a vague understanding and evolved to ignorance.

What does any of this have to do with identifying a persons skill? Does the secretary type 100 words per minute or does she specialize in typing on blue paper? A researcher in biotechnology is not a person who usually obtains 20 to 30 years of experience conducting research. Rather, they will begin their career as someone who is given the task of knocking out a target to effect a specific condition. The conditions are well documented so we assume the only way forward is to tackle the unknown of dealing with them. You will need molecular biology specialists, cell culture specialists, protein purification specialists, analytical machine operators, and so on. All of the people working in the laboratory are usually non-PhD research associates. Their careers begin with one of the above specialties and they advance their careers only in terms of years of experience. Typing is not enough. They must type on blue paper. For example, I've seen technicians with five years of experience running a Waters HPLC. The laboratory they apply to has Agilent HPLCs. They are out of the running. The skill is required by the researcher. It is not a skill that they must understand, thus they can make the mistake of not identifying what matters most. Do they want someone to effectively use the HPLC for its intended use or do they have an Agilent in their lab that no one knows how to turn on?

The researcher then, should be the person working to put all of the skilled technicians together to move from ignorance to understanding. The most in-demand researchers however are those who have the most patents and publications. The assumption here is that they have reached the level of understanding more often than those with less patents and publications. Science however is a superior way of thinking that takes great pains to distinguish between quantity and quality. Biotechnology is not science, it is a business. It needs experienced obedient workers to turn on the machines and do the paperwork. Research is handled by those who can most often get published and get patents. As a result the amount of useless patents and inaccurate publications have sky rocketed. The companies have had to return time and again to the point of ignorance, the point where research begins. It's not a bad place if you are a scientist. It is a place that fascinates and brings on the evolution of understanding. If you just spent $1.1 billion, such as Merck did on Sirna, it is a bad place to be. You just hired a bunch of people who all had experience typing on blue paper. Typing however, was not their specialty. Research was not their specialty. RNAi was.

Biotechnology has been reduced to mostly monoclonal antibody companies. They sometimes try to break up the molecule or make it more stable but these are bells and whistles that don't work very well. The business model remains, select target, make antibody, start clinical trials, partner or be acquired by big pharma. It's all just typing on blue paper specialists. Basic research, starting from a known ignorance, is the only way innovation will take place. Who has the courage to admit that they know how to type but they don't have any experience typing on blue paper?

Thursday, August 04, 2011

Dendreon heard the plea and they made a deal with death. But death is a son of a bitch. Now Dendreon is not going to be the next billion dollar biotech in the Northwest. The projection of $350 to $400 million in earnings for 2011 was a little off. It now looks like the number will be below $200 million.

What the leaders didn't count on was a lack of interest in what they were offering. Dendreon diagnosed their situation and found that the problem is primarily happening with small community-based physicians. As leaders of the biggest Cargo Cult in the Northwest, they had only been associating with "top academic centers that have been familiar with the product for years in clinical trials." They are having a hard time getting the dumb hick doctors on board. David Miller, an analyst with Biotech Stock Research in Seattle said, “Docs are not prescribing Provenge until they are certain they are going to be reimbursed.”

One reader of Xconomy had a slightly different version of the predicament Dendreon is in:

As an oncology practice administrator other than the high cost another issue is the data itself- patients may be hesitant to use a drug with 4 month survival when there are other options available. And if medicare remibursement decreases to ASP + 4 next year, these very expensive drugs could be difficult to justify administering in the community setting

Mitch Gold, the CEO of Dendreon said that the company needs to educate physicians about how the reimbursement process has been streamlined. The education in this case goes in the opposite direction. The market has educated Mitch Gold and the investors. In their arrogance, they forgot that the patient has a say in their health care. It's not just a paycheck for Dendreon, it's an end of life decision with options.

For the investors, the education came from the earnings call this week. For Mitch Gold and the insiders of Dendreon, the education took place on a daily basis. They just didn'tshare it with the investors. Someone asked the question back in March, "Why is Mitch selling his shares?" We have an answer.

Tuesday, August 02, 2011

My mom called with an idea. Her neighbors son was working down at the local university in the "Research Department". Why don't I apply and move closer to home?

The Research Department?

What Feynman was talking about in Cargo Cult Science, was research. He did not condemn all of psychology for flawed research methods. He spoke specifically to a problem in their experimental design. Not all people can spot experimental flaws, but it can be taught. For some this course would be easier than it is for others. Take for example, a recent Huffington Post article looking at the divorce rate for childless vs. couples with kids. It was mentioned that in 1950:

For couples without children, the divorce rate in 1948 was 15.3 per 1,000. Where one child was present, the estimate rate was 11.6 per 1,000. The figure thus continues to decrease, and in families with four or more children, it was 4.6. Altogether, the rate for couples with children was 8.8 per 1,000. In other words, the rate for childless couples was almost double the rate for families with children.

Over 2,000 comments turned up with people chiming in with their views on kids and marraige. One person however called attention to the notion that only 11 to 15 people per 1,000 were getting divorced. The divorce rate is currently around 50%.

The bias here got everyone talking about marriage and family. The "Research Department" guy picked up on a research issue.

Why don't they teach courses on how research is conducted. We can teach chemistry, biology psychology, and we assume that they understand where all of that information came from. Why don't we specifically get at the issue of research? In another HuffPo article a Gender Studies professor asked the question of whether or not men are what they used to be. She mentioned a study where men and women were asked questions about family and marriage. Once again, the comments section found people focusing on what makes a man a man. There were however those who brought up the fact that no such questionnaire was given to people in a previous era.

By all means, every University needs to establish a research department. Before a grad student begins conducting research for his/her professor, they need to do research without the bias they will encounter. Give students the tools they will need when facing a Bulfone-Paus or David Baltimore.

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My biotech career is merely a dream. In this dream we are all living on an Island where our ancestors once watched the westerners develop drugs that helped their people fight off disease and suffering. The westerners left and we are now donning their white lab coats and trying to create the drugs ourselves. We have their books, labs, beakers and a handful of drug targets they left behind. But nothing is working.